Gliomas are the most common primary brain tumors and occur at an incidence of almost 12 per 100,000 people (Landis et al., 1999). Diffuse astrocytoma may be classified (as per WHO classification) as low-grade diffuse (DA; Grade II), anaplastic (AA; Grade III) and glioblastoma (Grade IV; GBM), in the order of increasing malignancy (Mischel et al., 2001). Currently, these classifications are based on the observed histopathological characteristics of the tumor, which are sometimes subjective and inconsistent. GBM constitutes more than 80% of malignant gliomas (DeAngelis et al., 2001) and patients with GBM have a median survival of less than one year. Current treatments, including surgery, radiation therapy, and chemotherapy, unfortunately have not changed the natural history of these incurable neoplasms; and the prognosis of patients with GBMs has not improved significantly in the past 30 years (Davis et al., 1998). To find new diagnostic and therapeutic strategies, a better understanding of the biological pathway(s) leading to glial tumorigenesis is warranted.
Astrocytoma development is known to involve accumulation of a series of genetic alterations (Nagane et al., 1997) similar to other cancers. Identification of many of the genes involved in astrocytoma development, using standard molecular approaches, has helped to understand the process of astrocytoma genesis and progression (Louis and Gusella, 1995). Frequent amplification of epidermal growth factor receptor (EGFR) (Hill et al., 1999; Brock and Bower, 1997), platelet derived growth factor receptor (PDGFR) (Hermanson et al., 1992; Hermanson et al., 1996; Maxwell et al., 1990; Westermark et al., 1995; Fleming et al., 1992), amplification of chromosome 12q region, which carries the cdk4 gene (Nagane et al., 1997; Hill et al., 1999) and alterations in chromosomes 1p, 9p, 10, 17p, 19q, and 22q have frequently been found in these tumors. In addition, mutations in the tumor suppressor gene p53 were found to be associated with chromosome Yip alterations in low grade and progressive astrocytoma (Maher et al., 2001; Phatak et al., 2002). Inactivation of the cdk inhibitor p16 INK4a residing in chromosome 9p, is very common in sporadic astrocytoma, occurring in 50-70% of high-grade gliomas and 90% of GBM cell lines (James et al., 1991; Olopade et al., 1992). LOH in chromosome 10 is one of the most frequent alterations in GBM and is accompanied by the loss of PTEN/MMAC gene (Hill et al., 1999; Li et al., 1997).
GBMs are of two types: primary GBM (de novo type), which manifests in older patients (mean age: 55 yrs) as an aggressive, highly invasive tumor, usually without any evidence of prior clinical disease after a short clinical history of less than 3 months; secondary GBM (progressive type) is usually seen in younger patients (mean age: 40 yrs) and develops more slowly by malignant progression from diffuse (WHO grade II) or anaplastic astrocytoma (WHO grade III). Although some differences in the genetic lesions between these two GBMs have been identified, they are not sufficient enough to be used as differentiating markers considering the fact that the two types of GBMs have comparable clinical, genetic and biological characteristics (Kleihues et al., 2002). However, it is likely that these subtypes would respond differently to specific novel therapies as they are developed in the future (Kleihues and Ohgaki, 1999).
Despite all this information about astrocytoma, our understanding of astrocytoma development is not sufficient enough to improve prognosis for GBM patients. A more global, systematic understanding of expression patterns of various genes and their downstream gene products in astrocytoma will hopefully provide new diagnostic and therapeutic targets. Towards this, a number of studies have reported the gene expression profile of astrocytoma (Liau et al., 2000; Sallinen et al., 2000; Rickman et al., 2001; Ljubimova et al., 2001; Watson et al., 2001; Tanwar et al., 2002; Fathallah-Shaykh et al., 2002; Nutt et al., 2003; Wang et al., 2003; Godard et al., 2003).
It is also desirable to be able to target specific therapeutic modalities to pathogenetically distinct tumor types to maximize efficacy and minimize toxicity to the patient. (Golub et al., 1999; Kudoh et al., 2000). Previously, cancer classification has been based primarily on the morphological appearance of tumor cells. But this has serious limitations, because tumors with similar histopathgological appearance can follow significantly different clinical courses and show different responses to therapy. For example, based on histopathological appearance, astrocytoma grade IV cannot consistently be distinguished from astrocytoma grade III. Immunophenotyping for brain tumors has defined and refined diagnosis, e.g., distinguishing oligoastrocytoma from astrocytomas, and high-grade from low-grade astrocytomas. However, differential protein expression (GFAP, vimentin, synaptophysin, nestin) has not helped to improve therapeutic approaches. Prediction of transitions from low- to high-grade astrocytomas is difficult to make with currently available markers (De Girolami et al., 1994).
Tews and Nissen reported that immunohistochemical detection of various cancer-associated markers failed to reveal significant differential expression patterns among primary and secondary glioblastomas and precursor tumors; there was also no intra-individual constant expression pattern during glioma progression or correlation with malignancy. (Tews and Nissen, 1998-99). In contrast, class prediction for leukemia has been described based on monitoring gene expression profiles with DNA microarrays. (Golub et al., 1999).
But no class prediction capability, based on gene expression profiles, has been available heretofore for classifying high-grade gliomas to allow for optimizing treatment regimens. Zhang et al. (US Patent 20040053277) have identified a number of gene sets whose expression can accurately classify a glioma as glioblastoma (GBM), anaplastic astrocytoma (AA), anaplastic oligodendroglioma (AO) or oligodendroglioma (OL). However, these and other molecular markers currently in use are not capable of unambiguously identifying the subtypes of GBM. Mutations in p53 gene are reported to be associated with about 50% of grade WILL astrocytomas and secondary glioblastomas, but are seen only in 10-20% of primary glioblastoma (Campomenosi et al., 1996; Watanabe et al., 1997; Schmidt et al., 2002). Similarly, Epidermal growth factor receptor (EGFR), another marker routinely used in the classification of GBMs is found to be amplified in only 40% of all primary GBM cases and is rarely reported in secondary GBMs (Frederick et al., 2000). Microarray gene expression profiling of glioma allows simultaneous analysis of thousands of genes and is likely to identify molecular markers associated with tumor grade, progression and survival. Through cDNA microarray experiments, and subsequent validation with real-time quantitative PCR and/or immunohistochemistry, we have identified several distinct gene categories of transcripts over expressed in different set of astrocytoma. In addition, we have identified genes which characterize GBMs in general and primary GBMs in particular. Furthermore, we have also established the correlation between treatment response and the expression of the genes identified. Therefore, it is also a desideratum to be able to predict the presence of astrocytoma, type of glioblastoma and subtype of glioblastoma in the context of prognosis and, thus, to be able to administer appropriate treatment. These and other benefits are provided by the present invention.